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Data fusion in the presence of jamming

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3 Author(s)
Boyd, J.E. ; Cubic Defense Syst. Inc., San Diego, CA, USA ; Sworder, D.D. ; Hutchins, R.G.

In an environment subject to sudden change, the accuracy of tracking and prediction is strongly influenced both by the sensor architecture and by the quality of the individual sensors. This paper presents a performance analysis of an image-enhanced algorithm for both path following and covariance estimation in applications where the sensors are subject to jamming. For an illustrative trajectory, the performance of the algorithm is contrasted with an extended Kalman filter.

Published in:

Signals, Systems, and Computers, 1999. Conference Record of the Thirty-Third Asilomar Conference on  (Volume:2 )

Date of Conference:

24-27 Oct. 1999